Iris recognition is a form of biometric identification (ID) that uses mathematical pattern-recognition techniques on an image of an iris. The iris is a preferable body part to use for biometric ID because it contains complex patterns that are unique and can be seen from a distance. Traditional camera technology may be used to capture an image of an iris, often with subtle infrared illumination.
In order to isolate the iris, an algorithm first localizes the inner and outer boundaries of the iris (e.g., pupil and limbus). Eyelids, eyelashes, and specular reflections that often occlude parts of the iris may then be detected and excluded. Once the iris is isolated, statistical algorithms may be used to create a digital code from patterns found in the iris. These codes may be compared with stored codes in order to identify an individual.
U.S. Pat. No. 4,641,349, entitled “Iris Recognition Technology,” the content of which is incorporate by reference in its entirety, discloses a system and method for iris recognition. In particular, it discloses illuminating an iris to a particular size and extracting descriptors which can then be compared against those of a stored iris. This was a pioneering patent in the field of iris recognition developed by Dr. Flom, a named inventor on the current application.
U.S. Pat. No. 5,291,560, entitled “Biometric personal identification system based on iris analysis,” the content of which is incorporate by reference in its entirety, discloses another algorithm for iris recognition. In particular, it discloses extracting a bit pattern (an iris code) that encodes information from an iris image. A Gabor wavelet transform is used to filter the image and the result is a set of complex numbers that carry local amplitude and phase information about the iris pattern. For identification (e.g., one-to-many matching) or verification (e.g., one-to-one matching), the iris code can be compared to stored iris codes in a database. If the Hamming distance between the two codes is below a decision threshold, a positive identification has effectively been made.
However, known methods of iris recognition are susceptible to error. For example, a comparison of multiple images of the same iris may result in false negatives (or false positives between different iris images) because the images may be taken using different illumination intensities, with different camera lenses, or at different illumination angles or distances. Differences in ambient conditions make comparison of two images unreliable.
In addition, known methods are not capable of enrolling multiple biometrics. For example, some people may not have irises due to a medical condition (e.g., corneal blindness). In addition, newborn babies do not yet have developed irises and, as a result, known methods for iris recognition cannot be used to identify them.
Therefore, it would be beneficial to have a superior system and method for biometric identification. In particular, it is desirable to have a system for biometric identification capable of being employed on multiple forms of biometrics, for example, irises, ears, and fingerprints.